Selected topics in Pervasive Computing (Winter 2013/2014): Difference between revisions

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Selected topics in Pervasive Computing (Winter 2013/2014) (view source)

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(Created page with "== Details == {{CourseDetails |credits=180h, 6 ECTS |module=M.Inf.1221: Spezielle fortgeschrittenen Aspekte der Telematik |lecturer=[http://www.stephansigg.de Stephan Sigg] |time...")
 
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Depending on the interest of the students, the emphasis on these additional topics may differ.  
Depending on the interest of the students, the emphasis on these additional topics may differ.  


- Introduction (main focus)
Possible course topics (focus according to interest of students):
(basic introduction to Pervasive computing and its applications)
* Activity recognition
** Fundamentals of pattern matching
** Features and feature extraction
** Feature subset selection
** Polynomial curve fitting
** Parzen estimator
** k-NN
** SVM
** ANN


- Activity recognition (main focus)
* Context prediction
(Fundamentals of pattern matching, features and feature extraction, feature subset selection, polynomial curve fitting, parzen estimator, k-NN, SVM, ANN,...)
** Operations for single- and multi-dimensional context data
** Prediction architectures
** Context processing operations
** Prediction algorithms
*** ARMA
*** Kalman filter based
*** Approximate pattern matching
*** Markov predictors
*** Prediction with independent/principal component analysis
*** SOM
*** IPAM
*** ONISI 


* Security with noisy data / context-based security
** Entropy
** One-time-pad
** Random number generators
** Statistical tests
** Fuzzy commitment
** Fuzzy extractors
** PUFs


- Context prediction (extent depending on student interest)
* Networked objects
(operations for single- and multi-dimensional context data, prediction architectures, context processing operations, prediction algorithms (e.g. ARMA, Kalman filter based, approximate pattern matching, markov predictors, prediction with independent/principal component analysis, SOM, IPAM, ONISI),...) 
** A generic sensor node
** Sensor networks
** Communication protocols
** Collaborative and cooperative operations
** Body sensor networks


- Security with noisy data [Context-based security] (extent depending on student interest)
* Internet of Things
(Entropy, one-time-pad, random number generators, statistical tests, fuzzy commitment, fuzzy extractors, PUFs, ...)
** Communication technologies
 
** Sensors
- Networked objects (extent depending on student interest)
** RFID
(a generic sensor node, sensor networks, communication protocols, collaborative and cooperative operations, body sensor networks,...)
** Printed electronics
 
** Organic electronics
- Internet of Things (extent depending on student interest)
** Physical layer mathematical operations
(communication technologies, sensors, RFID, printed electronics, organic electronics, physical layer mathematical operations,...)
 
 
The purpose of this lecture is to discuss some advanced concepts in computer networking. This course is a research seminar (6 ECTS, 2 SWS), held on a weekly base and comprising the following components:
* Weekly paper reading and discussion + Weekly Presentation
* Final Presentation
* Final report
 
The material in the seminar, drawn mainly from the research literature from top tier journal/conference, like ToN, TPDS, SIGCOMM, SIGMETRICS, IMC, WWW, CoNEXT. The seminar topics include the following:
 
Clean slate architectures and future internet
Online Social Networking (Architecture, User Behavior, Data Collection, Data Analysis)
xxx


==Schedule==
==Schedule==
Ssigg
216

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